ReviewAntibiotics (Basel, Switzerland)2024
Brave New World of Artificial Intelligence: Its Use in Antimicrobial Stewardship-A Systematic Review.
Review in Antibiotics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.
- Artificial intelligence in antimicrobial stewardship: a systematic review and meta-analysis of predictive performance and diagnostic accuracy.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2025Pooled it
- Interventions to Reduce Antibiotic Prescribing in Small Animal Veterinary Practice: Evidence and Clinical Impact.Antibiotics (Basel, Switzerland) · 2026Review
- Recent advancements in artificial intelligence applications for the mitigation of antimicrobial resistance: challenges and opportunities.JAC-antimicrobial resistance · 2026Review
- Free Riding in Healthcare Through a Game-Theoretic Lens: A Cross-Domain Narrative Review and Conceptual Synthesis.Healthcare (Basel, Switzerland) · 2026Review
- Artificial Intelligence in Dialysis Therapies:Saudi medical journal · 2026Review
- Artificial intelligence for antimicrobial resistance: advancing reproducibility, interpretability, and clinical deployment.Briefings in bioinformatics · 2026Review
- Vancomycin resistance in gram-positive infections: evolutionary strategies of survival.Archives of microbiology · 2026Review
- The impact of artificial intelligence on the prescribing, selection, resistance, and stewardship of antimicrobials: a scoping review.BMC infectious diseases · 2025Article
- Seventeen Years of an Antibiotic Stewardship Programme: Trends in Antibiotic Prescribing and Gram-Negative Bacilli Susceptibility at a Quaternary Healthcare Institution.Antibiotics (Basel, Switzerland) · 2025Article
- Digital Twins in Pediatric Infectious Diseases: Virtual Models for Personalized Management.Journal of personalized medicine · 2025Review
- Comparative Evaluation and Performance of Large Language Models in Clinical Infection Control Scenarios: A Benchmark Study.Healthcare (Basel, Switzerland) · 2025Article
- Review
- Status and implications of the knowledge, attitudes and practices towards AWaRe antibiotic use, resistance and stewardship among low- and middle-income countries.JAC-antimicrobial resistance · 2025Review
- Implementation of Antimicrobial Stewardship Programs in Saudi Arabia: A Systematic Review.Microorganisms · 2025Review
- The Role of Artificial Intelligence and Machine Learning Models in Antimicrobial Stewardship in Public Health: A Narrative Review.Antibiotics (Basel, Switzerland) · 2025Review
- Integrating Machine Learning with MALDI-TOF Mass Spectrometry for Rapid and Accurate Antimicrobial Resistance Detection in Clinical Pathogens.International journal of molecular sciences · 2025Article
- The Role of ChatGPT and AI Chatbots in Optimizing Antibiotic Therapy: A Comprehensive Narrative Review.Antibiotics (Basel, Switzerland) · 2025Review
- Healthcare Professionals' Knowledge and Attitudes Toward Antimicrobial Stewardship Programs in Aseer, Saudi Arabia: A Cross-Sectional Study.Risk management and healthcare policy · 2025Article
- New antibiotics targeting Gram-negative bacilli.Le infezioni in medicina · 2025Review
- Fighting antimicrobial resistance in Brazil: strengthening diagnostic stewardship, antimicrobial stewardship, and policies for a healthier future.Frontiers in public health · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Antimicrobial resistance (AMR) is a growing public health problem in the One Health dimension. Artificial intelligence (AI) is emerging in healthcare, since it is helpful to deal with large amounts of data and as a prediction tool. This systematic review explores the use of AI in antimicrobial stewardship programs (ASPs) and summarizes the predictive performance of machine learning (ML) algorithms, compared with clinical decisions, in inpatients and outpatients who need antimicrobial prescriptions. This review includes eighteen observational studies from PubMed, Scopus, and Web of Science. The exclusion criteria comprised studies conducted only in vitro, not addressing infectious diseases, or not referencing the use of AI models as predictors. Data such as study type, year of publication, number of patients, study objective, ML algorithms used, features, and predictors were extracted from the included publications. All studies concluded that ML algorithms were useful to assist antimicrobial stewardship teams in multiple tasks such as identifying inappropriate prescribing practices, choosing the appropriate antibiotic therapy, or predicting AMR. The most extracted performance metric was AUC, which ranged from 0.64 to 0.992. Despite the risks and ethical concerns that AI raises, it can play a positive and promising role in ASP.
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.